Reinjin/Pelafalan_Huruf_Hijaiyah
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How to use ojisetyawan/whisper-base-ar-quran-ft-hijaiyah-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("audio-classification", model="ojisetyawan/whisper-base-ar-quran-ft-hijaiyah-2") # Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("ojisetyawan/whisper-base-ar-quran-ft-hijaiyah-2")
model = AutoModelForAudioClassification.from_pretrained("ojisetyawan/whisper-base-ar-quran-ft-hijaiyah-2")This model is a fine-tuned version of tarteel-ai/whisper-base-ar-quran on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5618 | 1.0 | 1336 | 0.5533 | 0.8956 |
| 0.5432 | 2.0 | 2672 | 0.4359 | 0.9203 |
| 0.0009 | 3.0 | 4008 | 0.4872 | 0.9181 |
| 0.0005 | 4.0 | 5344 | 0.3842 | 0.9360 |
| 0.0002 | 5.0 | 6680 | 0.4643 | 0.9315 |
| 0.0425 | 6.0 | 8016 | 0.3426 | 0.9551 |
| 0.0001 | 7.0 | 9352 | 0.3894 | 0.9450 |
| 0.0001 | 8.0 | 10688 | 0.4227 | 0.9461 |
| 0.0001 | 9.0 | 12024 | 0.4511 | 0.9506 |
| 0.0 | 10.0 | 13360 | 0.4117 | 0.9540 |
Base model
tarteel-ai/whisper-base-ar-quran